Harden IPMI power probe timeout

.gitignore

@@ -2,3 +2,4 @@
 .DS_Store
 dist/
 iso/out/
+build-cache/

audit/internal/platform/benchmark.go

@@ -1601,7 +1601,10 @@ func maxInt(a, b int) int {
 // queryIPMIServerPowerW reads the current server power draw via ipmitool dcmi.
 // Returns 0 and an error if IPMI is unavailable or the output cannot be parsed.
 func queryIPMIServerPowerW() (float64, error) {
-	out, err := satExecCommand("ipmitool", "dcmi", "power", "reading").Output()
+	ctx, cancel := context.WithTimeout(context.Background(), 10*time.Second)
+	defer cancel()
+	cmd := exec.CommandContext(ctx, "ipmitool", "dcmi", "power", "reading")
+	out, err := cmd.Output()
 	if err != nil {
 		return 0, fmt.Errorf("ipmitool dcmi power reading: %w", err)
 	}
@@ -1620,6 +1623,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
 	}
 	deadline := time.Now().Add(time.Duration(durationSec) * time.Second)
 	var samples []float64
+loop:
 	for {
 		if w, err := queryIPMIServerPowerW(); err == nil {
 			samples = append(samples, w)
@@ -1629,7 +1633,7 @@ func sampleIPMIPowerSeries(ctx context.Context, durationSec int) (meanW float64,
 		}
 		select {
 		case <-ctx.Done():
-			break
+			break loop
 		case <-time.After(2 * time.Second):
 		}
 	}

audit/internal/platform/benchmark_report.go

@@ -81,8 +81,12 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
 		b.WriteString("\n")
 	}
 
-	// ── Scoring methodology ───────────────────────────────────────────────────
+	// ── Methodology ───────────────────────────────────────────────────────────
-	b.WriteString("## Scoring Methodology\n\n")
+	b.WriteString("## Methodology\n\n")
+	fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline -> warmup -> steady-state -> interconnect -> cooldown phases.\n", result.BenchmarkProfile)
+	b.WriteString("- Single-GPU compute score comes from `bee-gpu-burn` on the cuBLASLt path when available.\n")
+	b.WriteString("- Thermal and power limits are inferred from NVIDIA clock-event counters plus sustained telemetry.\n")
+	b.WriteString("- `result.json` is the canonical machine-readable source for the run.\n\n")
 	b.WriteString("**Compute score** is derived from two phases:\n\n")
 	b.WriteString("- **Synthetic** — each precision type (fp8, fp16, fp32, fp64, fp4) runs alone for a dedicated window. ")
 	b.WriteString("Measures peak throughput with the full GPU dedicated to one kernel type. ")
@@ -286,13 +290,6 @@ func renderBenchmarkReportWithCharts(result NvidiaBenchmarkResult) string {
 		}
 	}
 
-	// ── Methodology ───────────────────────────────────────────────────────────
-	b.WriteString("## Methodology\n\n")
-	fmt.Fprintf(&b, "- Profile `%s` uses standardized baseline → warmup → steady-state → interconnect → cooldown phases.\n", result.BenchmarkProfile)
-	b.WriteString("- Single-GPU compute score from bee-gpu-burn cuBLASLt when available.\n")
-	b.WriteString("- Thermal and power limitations inferred from NVIDIA clock event reason counters and sustained telemetry.\n")
-	b.WriteString("- `result.json` is the canonical machine-readable source for this benchmark run.\n\n")
-
 	// ── Raw files ─────────────────────────────────────────────────────────────
 	b.WriteString("## Raw Files\n\n")
 	b.WriteString("- `result.json`\n- `report.md`\n- `summary.txt`\n- `verbose.log`\n")

iso/builder/VERSIONS

@@ -6,7 +6,7 @@ NCCL_CUDA_VERSION=13.0
 NCCL_SHA256=2e6faafd2c19cffc7738d9283976a3200ea9db9895907f337f0c7e5a25563186
 NCCL_TESTS_VERSION=2.13.10
 NVCC_VERSION=12.8
-CUBLAS_VERSION=13.0.2.14-1
+CUBLAS_VERSION=13.1.1.3-1
 CUDA_USERSPACE_VERSION=13.0.96-1
 DCGM_VERSION=4.5.3-1
 JOHN_JUMBO_COMMIT=67fcf9fe5a

iso/builder/bee-gpu-stress.c

@@ -33,7 +33,6 @@ typedef void *CUstream;
 #define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MAJOR 75
 #define CU_DEVICE_ATTRIBUTE_COMPUTE_CAPABILITY_MINOR 76
 #define MAX_STRESS_STREAMS 16
-#define MAX_CUBLAS_PROFILES 5
 #define MIN_PROFILE_BUDGET_BYTES ((size_t)4u * 1024u * 1024u)
 #define MIN_STREAM_BUDGET_BYTES ((size_t)64u * 1024u * 1024u)
 
@@ -689,6 +688,8 @@ static const struct profile_desc k_profiles[] = {
 #endif
 };
 
+#define PROFILE_COUNT ((int)(sizeof(k_profiles) / sizeof(k_profiles[0])))
+
 static int load_cublaslt(struct cublaslt_api *api) {
     memset(api, 0, sizeof(*api));
     api->lib = dlopen("libcublasLt.so.13", RTLD_NOW | RTLD_LOCAL);
@@ -1124,7 +1125,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
                                const char *precision_filter,
                                struct stress_report *report) {
     struct cublaslt_api cublas;
-    struct prepared_profile prepared[MAX_STRESS_STREAMS * MAX_CUBLAS_PROFILES];
+    struct prepared_profile prepared[MAX_STRESS_STREAMS * PROFILE_COUNT];
     cublasLtHandle_t handle = NULL;
     CUcontext ctx = NULL;
     CUstream streams[MAX_STRESS_STREAMS] = {0};
@@ -1134,7 +1135,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
     int active = 0;
     int mp_count = 0;
     int stream_count = 1;
-    int profile_count = (int)(sizeof(k_profiles) / sizeof(k_profiles[0]));
+    int profile_count = PROFILE_COUNT;
     int prepared_count = 0;
     size_t requested_budget = 0;
     size_t total_budget = 0;
@@ -1159,6 +1160,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         return 0;
     }
 
+    /* Count profiles matching the filter (for deciding what to run). */
     for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
         if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc &&
             (precision_filter == NULL || strcmp(k_profiles[i].block_label, precision_filter) == 0)) {
@@ -1172,18 +1174,31 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         return 0;
     }
 
+    /* Count all profiles active on this GPU regardless of filter.
+     * Used as the budget divisor so matrix sizes stay consistent whether
+     * running all precisions together or a single-precision phase. */
+    int planned_total = 0;
+    for (size_t i = 0; i < sizeof(k_profiles) / sizeof(k_profiles[0]); i++) {
+        if (k_profiles[i].enabled && cc >= k_profiles[i].min_cc) {
+            planned_total++;
+        }
+    }
+    if (planned_total < planned) {
+        planned_total = planned;
+    }
+
     requested_budget = (size_t)size_mb * 1024u * 1024u;
-    if (requested_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
+    if (requested_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
-        requested_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
+        requested_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
     }
     total_budget = clamp_budget_to_free_memory(cuda, requested_budget);
-    if (total_budget < (size_t)planned * MIN_PROFILE_BUDGET_BYTES) {
+    if (total_budget < (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES) {
-        total_budget = (size_t)planned * MIN_PROFILE_BUDGET_BYTES;
+        total_budget = (size_t)planned_total * MIN_PROFILE_BUDGET_BYTES;
     }
     if (query_multiprocessor_count(cuda, dev, &mp_count) &&
         cuda->cuStreamCreate &&
         cuda->cuStreamDestroy) {
-        stream_count = choose_stream_count(mp_count, planned, total_budget, 1);
+        stream_count = choose_stream_count(mp_count, planned_total, total_budget, 1);
     }
     if (stream_count > 1) {
         int created = 0;
@@ -1196,7 +1211,7 @@ static int run_cublaslt_stress(struct cuda_api *cuda,
         }
     }
     report->stream_count = stream_count;
-    per_profile_budget = total_budget / ((size_t)planned * (size_t)stream_count);
+    per_profile_budget = total_budget / ((size_t)planned_total * (size_t)stream_count);
     if (per_profile_budget < MIN_PROFILE_BUDGET_BYTES) {
         per_profile_budget = MIN_PROFILE_BUDGET_BYTES;
     }
@@ -1424,7 +1439,17 @@ int main(int argc, char **argv) {
     ok = run_cublaslt_stress(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, precision_filter, &report);
 #endif
     if (!ok) {
-        if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, size_mb, &report)) {
+        if (precision_filter != NULL) {
+            fprintf(stderr,
+                    "requested precision path unavailable: precision=%s device=%s cc=%d.%d\n",
+                    precision_filter,
+                    name,
+                    cc_major,
+                    cc_minor);
+            return 1;
+        }
+        int ptx_mb = size_mb;
+        if (!run_ptx_fallback(&cuda, dev, name, cc_major, cc_minor, seconds, ptx_mb, &report)) {
             return 1;
         }
     }

iso/builder/build.sh

@@ -873,9 +873,37 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
 
     CUBLAS_CACHE="${DIST_DIR}/cublas-${CUBLAS_VERSION}+cuda${NCCL_CUDA_VERSION}"
 
+    echo "=== bee-gpu-burn FP4 header probe ==="
+    fp4_type_match="$(grep -Rsnm 1 'CUDA_R_4F_E2M1' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
+    fp4_scale_match="$(grep -Rsnm 1 'CUBLASLT_MATMUL_MATRIX_SCALE_VEC16_UE4M3' "${CUBLAS_CACHE}/include" 2>/dev/null || true)"
+    if [ -n "$fp4_type_match" ]; then
+        echo "fp4_header_symbol=present"
+        echo "$fp4_type_match"
+    else
+        echo "fp4_header_symbol=missing"
+    fi
+    if [ -n "$fp4_scale_match" ]; then
+        echo "fp4_scale_mode_symbol=present"
+        echo "$fp4_scale_match"
+    else
+        echo "fp4_scale_mode_symbol=missing"
+    fi
+
     GPU_STRESS_NEED_BUILD=1
-    if [ -f "$GPU_BURN_WORKER_BIN" ] && [ "${BUILDER_DIR}/bee-gpu-stress.c" -ot "$GPU_BURN_WORKER_BIN" ]; then
+    if [ -f "$GPU_BURN_WORKER_BIN" ]; then
         GPU_STRESS_NEED_BUILD=0
+        for dep in \
+            "${BUILDER_DIR}/bee-gpu-stress.c" \
+            "${BUILDER_DIR}/VERSIONS"; do
+            if [ "$dep" -nt "$GPU_BURN_WORKER_BIN" ]; then
+                GPU_STRESS_NEED_BUILD=1
+                break
+            fi
+        done
+        if [ "$GPU_STRESS_NEED_BUILD" = "0" ] && \
+            find "${CUBLAS_CACHE}/include" "${CUBLAS_CACHE}/lib" -type f -newer "$GPU_BURN_WORKER_BIN" | grep -q .; then
+            GPU_STRESS_NEED_BUILD=1
+        fi
     fi
 
     if [ "$GPU_STRESS_NEED_BUILD" = "1" ]; then
@@ -889,6 +917,12 @@ if [ "$BEE_GPU_VENDOR" = "nvidia" ]; then
     else
         echo "=== bee-gpu-burn worker up to date, skipping build ==="
     fi
+    echo "=== bee-gpu-burn compiled profile probe ==="
+    if grep -aq 'fp4_e2m1' "$GPU_BURN_WORKER_BIN"; then
+        echo "fp4_profile_string=present"
+    else
+        echo "fp4_profile_string=missing"
+    fi
 fi
 
 echo "=== preparing staged overlay (${BUILD_VARIANT}) ==="